The present invention relates to a conversational sentence translation apparatus for translating a conversational sentence in a first language into a second language by making use of previously registered conversational sentence examples.
Nowadays, with increased opportunities of going abroad for sightseeing and other purposes, there have been published a variety of conversation example collections in which many conversational expressions with their translations are collected so as to help one to be successful with conversations in foreign countries. Also, conversational sentence translation apparatuses have been commercially available in which those conversation example collections are stored as electronic data, so that a conversational sentence example in one language is selected through key operation or the like by the user and that a previously prepared translation in another language of the selected conversational sentence example is automatically displayed.
Generally, such a conversational sentence translation apparatus is designed not to translate a freely prepared input, sentence in a first language into an equivalent in a second language by a machine translation system and output the obtained translation. Instead it selects one of the previously prepared conversational sentence examples and display a previously prepared translation of the selected conversational sentence example. That is, a sentence example selection method is adopted. The reasons for this are that:
(1) A machine translation system that translates free sentences in a first language is difficult to implement in a portable form because of its intricacy; and
(2) Because of its technical immatureness in translating free sentences, translations by the machine translation system result in poor translation quality, in comparison with the sentence example selection method wherein previously prepared translated sentences of previously prepared conversational sentence examples are outputted.
Meanwhile, for the sentence example selection method, it is desirable to store a large number of conversational sentence examples with a view to matching a large number of situations of use. Further, as proposed in Japanese Patent Publication SHO 61-16117, if the stored conversational sentence examples contain replaceable portions so that the replaceable portions of the conversational sentence examples can be replaced with another, the scope within which the registered conversational sentence examples are applied can be expanded. However, the greater the number of conversational sentence examples, the more troublesome and difficult it becomes to select a target conversational sentence example from among the conversational sentence examples registered in the conversational sentence translation apparatus.
Thus, to solve such disadvantages, as seen in, for example, Japanese Patent Publication SHO 60-24501, there has been adopted a method that the conversational sentence examples are previously classified according to categories and stored in categories. By this method, the search scope for a desired conversational sentence example is narrowed by specifying a category corresponding to the situation of use.
Another method for narrowing the search scope is to specify a keyword so that a registered conversational sentence example containing the keyword is selected. For example, in Japanese Patent Publication SHO 58-58714, matching is made between an input keyword and words contained in each registered conversational sentence example, and a translation of a conversational sentence example using a word coincident with the keyword is outputted as the translation of the target conversational sentence example. In still another method, disclosed in Japanese Patent Laid-Open Publication HEI 5-324702, label information is previously added to each conversational sentence example, and a conversational sentence example to which specified label information has been added is selected.
However, in the conventional conversational sentence translation apparatus, an attempt to store even larger numbers of conversational sentence examples for a wider coverage of conversational situations would cause the problem of a difficulty in finding out a target conversational sentence example to arise again.
For example, in the method disclosed in Japanese Patent Publication SHO 60-24501, in which conversational sentence examples are previously stored in a classified manner, the number of categories to be stored is increased or the number of conversational sentence examples belonging to each category is increased. Therefore, a target conversational sentence example is difficult to find out. Further, to solve this disadvantage, there has been proposed a method in which the categories are built up hierarchically by creating sub-categories within one category so that the number of categories or conversational sentence examples to be selected in each layer of the hierarchy is decreased. Unfortunately, also in this case, according as the number of layers in the hierarchy of categories increases, the handling until the target conversational sentence example is reached becomes more complicated and therefore it becomes more difficult to find out the target conversational sentence example.
Further, in the above conversational sentence translation apparatus in which conversational sentence examples are classified according to categories, since the categorical classification of the conversational sentence examples is carried out by the developer of the apparatus, a target conversational sentence example does not necessarily belong to the category that the user has expected. This makes the apparatus inconvenient for use in some cases. Besides, building up a hierarchical categorical system as described above would add to the inconvenience in use.
In contrast to this, in the method in which a conversational sentence example is retrieved by the use of a keyword, as described before, a conversational sentence example is retrieved with an input word taken as the keyword. For example, when a Japanese word "KAGI" (which means "key" in English) is entered as the keyword, a conversational sentence example "KAGI WO KUDASAI" (which means "Give me the key.") or "KAGI WO NAKUSHIMASHITA" (which means "I have lost the key.") containing the keyword "KAGI" is selected. In another example of this method, keywords are previously added to the conversational sentence examples, and conversational sentence examples to which the keyword "KAGI" has been added are selected. With this method, when the user enters a word that makes the core of a conversational sentence example to be retrieved, conversational sentence examples associated with the keyword are selected and displayed. Then, the user is allowed to specify a target conversational sentence example more directly than when the user traces the categories until the target conversational sentence example is reached.
Unfortunately, in this method utilizing the keyword as well, as the number of stored conversational sentence examples increases, larger numbers of conversational sentence examples would be selected for one keyword, resulting in a difficulty in making a choice out of them. A solution to this problem may be to narrow the search scope for conversational sentence examples by specifying a plurality of keywords. However, this approach would involve an issue of how and which words should be chosen as keywords from among words constituting the conversational sentence example that the user wants to set.
As shown above, the conversational sentence translation apparatuses of the prior art as have been suffering from problems due to an input method, which is far from the ideal input method that allows a natural sentence to be entered in a first language.
The above problems occur when the user selects a target sentence that the user wants to input and translate, from among the previously registered conversational sentence examples. The user, in choosing a conversational sentence example, is inevitably required to be always conscious of "which category the sentence that the user wants to translate belongs to" or "which and what keyword the user should use for search".